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README.md ADDED
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+ ---
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+ library_name: transformers
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+ language:
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+ - yo
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+ license: apache-2.0
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+ base_model: openai/whisper-small
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+ tags:
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+ - whisper-event
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+ - generated_from_trainer
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+ datasets:
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+ - mozilla-foundation/common_voice_17_0
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+ metrics:
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+ - wer
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+ model-index:
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+ - name: Harcuracy/whisper_bouesti_asr
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+ results:
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+ - task:
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+ name: Automatic Speech Recognition
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+ type: automatic-speech-recognition
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+ dataset:
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+ name: Common Voice 17.0
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+ type: mozilla-foundation/common_voice_17_0
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+ config: yo
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+ split: test
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+ args: yo
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+ metrics:
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+ - name: Wer
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+ type: wer
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+ value: 51.038251366120214
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # Harcuracy/whisper_bouesti_asr
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+
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+ This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 17.0 dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.7570
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+ - Wer: 51.0383
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 1e-05
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+ - train_batch_size: 8
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+ - eval_batch_size: 8
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+ - seed: 42
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+ - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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+ - lr_scheduler_type: linear
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+ - training_steps: 1000
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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Wer |
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+ |:-------------:|:------:|:----:|:---------------:|:-------:|
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+ | 0.4516 | 0.8711 | 250 | 0.7315 | 55.8806 |
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+ | 0.2582 | 1.7422 | 500 | 0.7210 | 51.2232 |
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+ | 0.1496 | 2.6132 | 750 | 0.7389 | 50.6852 |
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+ | 0.0913 | 3.4843 | 1000 | 0.7570 | 51.0383 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.47.0
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+ - Pytorch 2.5.1+cu121
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+ - Datasets 3.2.0
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+ - Tokenizers 0.21.0
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